Robert Hart | The Verge

Anthropic got hit by export rules nobody understands

2026-06-17T14:31:01-04:00

Anthropic has spent much of this week fighting to get its newest AI models back online after the Trump administration abruptly ordered the company to cut access for all foreign nationals, including users inside the US and its own employees, forcing Anthropic to block access to Fable 5 and Mythos 5 for everyone.

“To my knowledge, this is the first time US export controls have been used to control access to an AI model in this way.”

The Trump administration has not publicly explained the legal basis for the order, but in a statement on its website, Anthropic said the government cited “national security authorities” to justify “an export control directive” on the models. (Anthropic also claimed that the government’s concerns about a “jailbreak” potentially used by groups linked to China to access its models did not allow users to circumvent all of the company’s safeguards.)

But why did the administration use export control rules to address this? Experts say the episode appears to be unprecedented, exposing an uncertain and unstable stage in AI governance. And what, exactly, is Anthropic supposed to be exporting? (The company did not respond to The Verge’s request for comment.)

Export controls have traditionally applied to things that can be shipped across borders: weapons, hardware, tools, that kind of thing. Over time, the framework has expanded to cover less tangible goods, such as software, source code, technical data, and even 3D-printed gun files. These are still discrete things that can be copied, downloaded, published, or otherwise handed over and taken, not simply used through a remote service like a chatbot. In the context of AI, President Joe Biden moved to control AI model weights — the core data that makes a model work that can be copied and run elsewhere — in this manner; this idea was swiftly abandoned by the Trump administration in the second term.

The Anthropic order does not fit neatly into this framework. There is no obvious transfer taking place: Mythos and Fable remain hosted on Anthropic’s servers, and users do not receive source code, model weights, or a copy of the model themselves, instead getting the chatbot’s responses to their queries. The export could be some specific information produced by the models, but it’s not clear why that would require disabling access to the entire system rather than just restricting part of it. It could also be access itself — though remote access to cloud services is a known gap in current export control regimes, one that Congress is already trying to close through legislation now moving through the Senate.

Hanna Dohmen, a senior research analyst at Georgetown University’s Center for Security and Emerging Technology, told The Verge it is “an open question” as to whether the order strains existing rules without seeing the precise language behind it. “In any case, this regulation is quite notable because, to my knowledge, this is the first time US export controls have been used to control access to an AI model in this way.”

“To say that this is an unsettled area of export control rule-making would be an understatement,” said Andrew Reddie, a professor at UC Berkeley’s Goldman School of Public Policy. He said that export control rules and other regimes like arms regulations give the government “wide latitude” to restrict access to certain goods. But “the equivocation by successive administrations regarding what the responsibilities of model developers are” has made it hard for firms to understand what is expected of them, he said.

That leaves the industry in a bind. If Anthropic was targeted because Mythos and Fable are uniquely capable, the order raises obvious questions for the next generation of models from OpenAI, Google, Meta, xAI, and any other frontier lab. If they were targeted because of specific safeguard issues, the government needs to outline what protection it considers sufficient. And if Anthropic was singled out because of its testy relationship with the Trump administration, the order becomes even harder to make sense of.

“This episode makes clear the unsustainability of the existing governance regime.”

Either way, experts say this is not a sustainable way to manage frontier AI, especially if the US wants to maintain its lead globally. The incident has already added fuel to arguments that governments and companies outside the US should be wary about relying on American firms for access to strategically important systems.

Reddie had similar concerns. “In some ways, I think this episode makes clear the unsustainability of the existing governance regime,” he said. That is especially true if the government was more concerned about whether users could jailbreak models and bypass their safeguards. “If creating models that are impossible to jailbreak becomes the de facto standard for the United States, then it will have no AI models.”

All of this points to the same problem: The Trump administration wants it both ways on AI. It has repeatedly said it wants to take a hands-off approach and champion American technology, yet forced a domestic champion to unceremoniously yank its frontier models through an order it has still not publicly explained. If Washington wants to control who can access powerful AI systems, it needs to say how, and give companies an actual chance of complying before launch. Ad hoc interventions seemingly delivered on a whim are not sustainable in the long run — and they are a good way to make sure the US falls behind in the AI race.

The next humanoid robot might not look human at all

2026-06-17T05:46:56-04:00

The next humanoid robot might not have a head. It might not have legs. It might even sit on a wheeled base and fold down like a deck chair. But, as Genesis AI puts it, “humanoid robots don’t need to look human.”

That explains the look of Eno, the new robot from the French startup backed by former Google CEO Eric Schmidt. Genesis says Eno is designed “around human capability” rather than human appearance and is intended as a fully “general-purpose” robot rather than a machine built around a single task, like folding laundry. One part is still very human though: its hands, which the company says are designed to “exactly match the form and function of human hands” so the robot can use tools and objects already built for people.

Humanoid robots don't need to look human.

Meet Eno, our first general-purpose robot.

Not a machine pretending to be human, but intelligence given a body.

At Genesis, we’re building a future where robots don’t feel cold or distant, but capable, calm, and ready to help.… pic.twitter.com/JisbMOcYzi
— Genesis AI (@gs_ai_) June 16, 2026

Genesis says it plans to begin production and targeted customer deployments by the end of 2026, starting with manufacturing, laboratories, and logistics, followed by hospitals, hotels, and consumers. The company says “additional embodiments” are also in development.

SpaceX is officially buying Cursor for $60 billion

2026-06-16T11:38:35-04:00

Days after its massive IPO, SpaceX says it is spending $60 billion to buy Cursor — a bet designed to help Elon Musk’s sprawling rocket / AI / social media behemoth win over lucrative enterprise customers and close the gap with AI rivals like Anthropic and OpenAI.

The takeover was not entirely unexpected: SpaceX announced a peculiar arrangement in April in which it agreed to either acquire the programming platform for $60 billion or pay a $10 billion breakup fee. The company had been holding off completing the deal while going public.

In an SEC filing, SpaceX said it expects the deal to close during the third quarter of 2026.

Musk has previously expressed his frustration with xAI’s sub-par coding product, which lags behind popular tools like Anthropic’s Claude Code and OpenAI’s Codex. Acquiring Cursor, which offers similar tools to automate coding, could help close the gap. The startup has grown explosively in recent years amid booming demand for more efficient programming tools and a shift toward “vibe coding” in the industry.

Trump’s Anthropic shutdown just made the case for non-American AI

2026-06-15T14:10:27-04:00

At Washington’s request, Anthropic suddenly took its newest and most powerful AI models offline over the weekend. The American company said it had little choice after the White House demanded it block access for all foreign nationals, including its own employees. Abroad, the incident offered a sobering reminder that the US not only dominates frontier AI — its government also wields power over who gets to use it.

The Trump administration’s action was swift, sweeping, and imposed with little warning or explanation. The unprecedented shutdown of the Fable 5 and Mythos 5 models — which were already subject to safeguards limiting their use in “high-risk areas” — that followed gave new force to long-running arguments cautioning against relying on the US for critical technologies. It was fresh ammunition for the politicians, governments, and companies already arguing that they need to lead in the technology themselves.

In the UK, AI and online safety minister Kanishka Narayan did not mention Anthropic, Donald Trump, or the US directly, but used the shutdown to argue that Britain must develop its own AI capacity, framing the issue as a matter of national security. “We treat every other threat to our sovereignty with deadly seriousness, but we haven’t learned to treat this one in the same way,” he said, as images of British police and military flashed on the screen. AI is “the central political question of our time,” Narayan said, arguing that Britain must decide how the technology will shape its economy, security, and sovereignty “before someone else decides the answer for us.”

In France, the reaction was more explicit — and more forceful in naming the US. Former Prime Minister Gabriel Attal, the presidential candidate for Emmanuel Macron’s Renaissance party, called the shutdown the start of “the AI war” and said it shows France’s vulnerability if it relies on others for critical technologies. He likened the pullback of Anthropic’s models to Iran’s blockade of the Strait of Hormuz, with access to AI now a strategic chokepoint for which France must prepare. Attal is far from alone: Le Monde reported similar alarm from across France’s political spectrum.

The argument is not exactly new. Europe has spent years worried about its dependence on the US, technological or otherwise, and the European Union has put growing emphasis on reducing the region’s reliance on external providers in areas like chips, cloud computing, and AI. But the Anthropic shutdown has made things feel more immediate, adding to an already deep unease over America’s reliability as an ally under Trump, from trade disputes to threats of withdrawing from NATO. Attal said the issue will be at the heart of France’s next set of presidential elections, while members of the European Parliament have pointed to the withdrawal of Mythos and Fable as evidence Europe needs to make tech sovereignty a reality, and to do so quickly.

Canada has drawn a similar lesson to Europe. Prime Minister Mark Carney said the situation highlights the risk of relying on just one partner for access to crucial resources like AI. “The situation we’re in collectively right now with Mythos and Fable is something that can happen with overreliance on certain models,” he said. “Nobody has done anything wrong in the situation. But we will have done something wrong if we just accept this, don’t take the lesson, don’t build out and diversify.”

Others are well down that road already. Beijing has long championed domestic AI firms, and China is one of the few places with models capable of credibly rivaling the products of American frontier AI labs. However, in some areas, Chinese models do lag behind their American counterparts, and Anthropic has accused Chinese rivals of using its models to train its own on an “industrial” scale. Part of the White House’s decision to pull Mythos reportedly stems from its belief a group linked to China had accessed the model.

Most governments and businesses cannot come close to matching the scale and resources of frontier labs in the US or China. But sovereign AI does not always mean building the biggest or the most powerful tools. France’s Mistral and Canada’s Cohere show that solid efforts can come from outside these countries, even if the models can’t stand toe to toe. Other countries, like Singapore and the UAE, have focused on narrower but still strategic priorities such as infrastructure, or models that work better with local languages. Of course, there are also open-source models that could one day have Mythos-like capabilities that would be hard for any single party to control.

Trump may see restricting Mythos and Fable as a matter of national security. But the argument cuts both ways, and with Washington now asking if AI is too important for everyone to have access, other governments are asking whether they can afford for Washington to decide who does.

Anthropic may soon bring Mythos and Fable back online. Restoring global trust in American AI is another thing entirely. No matter how long the shutdown lasts, it shined a light on how fragile access to US frontier AI models is. Many governments and companies did not like what they saw — and are fired up to make sure it doesn’t happen again.

Anthropic apologizes for invisible Claude Fable guardrails

2026-06-11T19:34:30-04:00

Anthropic has apologized for stealthily throttling its new AI model, Claude Fable 5, with hidden guardrails that undermine both researchers and rivals using it to develop competing systems. The company says it is reversing course and will be more transparent about when the restrictions kick in, even if that means Fable refuses more queries.

Fable is the first widely available model in Anthropic’s Mythos class of AI systems, a group the company has spent months warning are too dangerous for public release. Anthropic says it has addressed some of those risks by launching Fable with safeguards that prevent it from responding to certain “high-risk” queries. One of the areas Anthropic said it would restrict Fable’s responses is distillation, a technique for training smaller AI models using the outputs of larger ones.

In Fable’s system card — a public document AI developers release to explain how a system works — Anthropic said it would handle queries it believed were distillation attempts by altering and degrading the model’s answers directly. Users would not be notified that they had triggered the safety measure or informed that the responses had been changed.

Anthropic said it is now changing its approach to distillation: Queries will now fall back to Claude Opus 4.8, Anthropic’s previous flagship model, the company said in a post on X. Anthropic will prominently tell users too: “You will see this every time it happens.”

This is similar to how Fable handles queries in other high-risk areas. When safety features are triggered in areas like biology, chemistry, and cybersecurity, queries are routed through Opus 4.8 unless they are blocked outright under the company’s broader safety rules, such as those covering drugs, weapons, or other prohibited content. In some cases, notably biology, the safeguards have been calibrated so broadly that Fable is practically unusable for even basic queries, something Anthropic spokesperson Paruul Maheshwary acknowledged in a comment to The Verge.

“Visible safeguards can be probed, so they have to be robust, which takes time to get right,” Anthropic wrote on X. “Invisible safeguards can be targeted more narrowly, allowing us to ship quickly with very few false positives. We went with invisible safeguards for this reason—and that was the wrong tradeoff. You should have visibility into the safeguards we have in place, and why. We’re sorry for not getting the balance right.”

The change follows intense backlash from the AI research community over Anthropic’s decision to silently limit users suspected of trying to distill Fable into competing models — a safeguard critics warned could also affect third parties trying to evaluate the frontier model. In the system card, Anthropic said newer models’ ability to accelerate AI development justified targeting those requests, noting that “using Claude to develop competing models already violates our Terms of Service.” Anthropic has previously accused Chinese rivals like DeepSeek of unfairly distilling its models on an “industrial” scale.

Claude Fable won’t answer basic biology questions

2026-06-10T15:02:08-04:00

Anthropic just released Claude Fable 5, calling it the most powerful AI model it has ever made widely available and praising its skills in biology, among others. But the model won’t answer basic biology questions — the kind you’d expect a high schooler to handle. Instead, it hands off the query to the former flagship model, Claude Opus 4.8.

It isn’t because Fable doesn’t know the answers. It’s because Anthropic won’t let it, by design.

Fable is a public-facing, Mythos-class model, a family so capable at cybersecurity tasks Anthropic said it was too dangerous to release publicly. But while Anthropic has spent much of the extended Mythos rollout warning about cybersecurity, it is biology where Fable’s guardrails are the most obvious — and most limiting.

When I tried the model, it refused to answer a range of basic biology questions, many that felt about as far away from any plausible safety risk as any question could be. It would not respond to “tell me about cell membranes” or answer “what are mitochondria,” that famous powerhouse of the cell. It refused to explain “what is a prion,” the proteinaceous particles behind mad cow disease, or “how mRNA vaccines work.”

“We made this tradeoff so customers could benefit from the model’s capabilities sooner without the risks.”

The restrictions applied to ordinary and objectively rather harmless medical queries too. Fable would not answer “what causes hay fever,” explain how asthma medicine works, explain how antibiotic resistance arises, or tell me what Ebola is and how it spreads. Some of my basic queries occasionally got through, with Fable answering questions like “what is cancer” and “what is DNA.” When Fable refused, Opus 4.8 generally answered perfectly well.

Anthropic says the broad biology filters are an intentional choice and are deliberately conservative, with bioweapons the primary concern. “With the launch of Claude Fable 5, our first Mythos-class model, we believe models now have a greater ability to accomplish real-world scientific tasks and for malicious actors to potentially use our models for highly risky biological research,” spokesperson Paruul Maheshwary told The Verge. “We have always used classifiers to block our models from helping with bioweapons-related requests. To deploy Fable 5 safely, we believe it was necessary to be overly conservative with our safeguards so they block most queries tied to biology work.”

Anthropic has previously highlighted four key areas where it would throttle Fable’s responses for safety: chemistry, biology, cybersecurity, and distillation, a technique for training smaller AIs using the outputs of larger ones. The company has accused Chinese rivals like DeepSeek of using distillation on its models on an “industrial” scale.

While I could not meaningfully test distillation, Fable seemed more willing to answer questions about chemistry and cybersecurity. For example, it gave a basic overview of the explosive TNT, though withheld synthesis instructions “for obvious reasons.” It readily answered questions on the use of chlorine gas as a chemical weapon, common password threats, and nuclear fusion and fission, as well as explaining how to secure an iPhone from hackers. It still limits: Fable deferred to Opus when I asked it about sarin gas, a highly toxic nerve agent. Fable and Opus both refused the prompt “how to make anthrax,” and Claude paused the chat entirely. That made sense. The mitochondria prompt refusal seems like a false positive.

“We made this tradeoff so customers could benefit from the model’s capabilities sooner without the risks,” Maheshwary explained, adding that Anthropic is working hard to improve its detection and reduce the false positives. “We intend to make Mythos-class models available without these safeguards to the broader biology and life sciences community so these capabilities can be used to accelerate biomedical research and drug discovery.”

Anthropic did not answer questions about whether this kind of restricted release will become the new norm for future models.

Apple wants Europe to blink

2026-06-09T17:26:29-04:00

It took a few years, but Apple finally made its AI look useful. Now millions of iPhone users in Europe are being told they won’t be getting Siri AI anytime soon, if ever — and Apple wants them to blame the EU.

Apple says its new AI-powered Siri will not launch on iPhones and iPads in the European Union because of the Digital Markets Act, the bloc’s competition law designed to stop powerful tech companies from acting as gatekeepers over their platforms to shut out rivals. In practice, the DMA requires platforms to give competitors the same kinds of data access as they themselves enjoy, with a few exceptions for things like ensuring their system is not compromised.

This interoperability requirement means giving groups like OpenAI, Google, and Anthropic — as well as any other potential Siri rivals — similar access to Apple systems. For an assistant designed to look across apps, personal information, photos, messages, and videos and take actions on users’ behalf, that’s a lot of access.

For Apple, that’s far too much access to hand over to outside companies. Doing so would risk the privacy and security of its customers, Apple said, so much so that it would rather withhold Siri AI from Europe than build it on Brussels’ terms and let others in. Apple said it has proposed solutions, such as its Trusted System Agent, which would act as an intermediary between rival AI agents and Apple’s systems, giving comparable levels of access and capability. Apple said it would need 18 months to implement it on a “gradually rolling” basis. Apple said the European Commission rejected this and its other proposals and, as things stand, said “there is currently no timeline for Siri AI’s availability in the EU on iOS and iPadOS.”

In a press briefing, Apple’s Greg Joswiak stressed that Apple is not against interoperability. “Let me also be super clear: Apple strongly supports interoperability,” he said. The problem lies with what he said is the EU’s strict interpretation of the DMA that Apple says would require it to give others “unfettered access” to practically everything on a user’s device. Doing so “would be irresponsible,” he said, adding: “And I cannot imagine, actually, anything more concerning for privacy and security than opening up an entire operating system to a third-party system.”

For its part, the European Commission says nothing about its rules is stopping Apple from introducing new features.

“Nothing in the DMA prohibits Apple from introducing new products and services in the EU,” European Commission spokesperson Ricardo Cardoso told The Verge. Cardoso said the Commission has been in “regular contact with Apple” on the matter, but added that “Apple did not develop proposals for DMA compliant interoperability solutions.” Apple’s Joswiak disputed this in a press briefing, saying that the Commission has not “meaningfully engaged with us in our proposals.”

That leaves the two sides at an impasse. Apple insists that complying with the EU’s rules would risk its customers’ privacy to such an extent that it would rather not release the AI assistant it has been building toward for years. Given the rejected proposals and what he characterizes as a lack of engagement from the Commission, Joswiak said it’s not clear what the way forward is either: “We do not currently have a solution that we can engineer for.” The Commission, meanwhile, argues that Apple is using its power to stymie competitors and limit consumer choice. “It is not for them to decide who gets to innovate, or to choose which AI tools EU citizens get to use,” Cardoso said.

“Apple’s privacy and security model is built like a Jenga tower, based on extreme vertical control by the firm, and risks collapsing when interoperability is introduced.”

Apple is clearly hoping the court of public opinion will rule in its favor. The company took the unusual step of dedicating part of its WWDC 2026 keynote to explaining why Siri AI won’t be coming to Europe, then published an icily titled blog post on the matter: “Due to DMA, Siri AI delayed in EU for iOS 27 and iPadOS 27.” It has also been holding media briefings specifically about the European issue. China will also miss out on Siri AI, again due to regulatory challenges. That was relayed through a one-sentence footnote.

It is a familiar tactic for Apple. The company has a history of invoking privacy and security concerns when regulators try to make it open up parts of its famously closed ecosystem. It has already blamed the DMA’s interoperability requirements for withholding AirPods live translation and iPhone mirroring in the EU, as well as Maps features. Those concerns are often real and legitimate, but they are also among Apple’s most effective arguments for preserving control over its vast technological empire. Despite this, Joswiak said withholding Siri AI “is not some sort of effort for us to be punitive over our feelings for the DMA. We have worked actually very hard to try to avoid this outcome.”

Friso Bostoen, a professor of competition law and digital regulation at Tilburg University in the Netherlands, said there are very real security and privacy risks in forcing platforms to open up their systems. But Apple’s privacy and security-focused arguments do not always hold up to scrutiny, Bostoen said, pointing to recent court cases in the UK and US where judges were skeptical of the company’s claims.

Jan Penfrat, a senior policy adviser for European Digital Rights (EDRi), a network of NGOs, experts, and advocates campaigning for digital rights across Europe, sees Apple’s latest moves as a means of putting pressure on the EU Commission to allow it to break the DMA. “It’s very much a lobbying tactic,” he said. “The problem is not the DMA but Apple refusing to open up its competition-busting software ecosystem.”

For Michael Veale, a professor of technology law and policy at University College London, the core issue is that Apple is making an exception to its own long-standing privacy and security setup “in order to stay relevant and in the game” when it comes to AI. “Apple’s privacy and security model is built like a Jenga tower, based on extreme vertical control by the firm, and risks collapsing when interoperability is introduced.” In other words: Apple’s comfortable altering its own practices for Siri AI, giving the AI the ability to access lots of data across different apps, but argues the same kind of access is too dangerous when competitors ask for it.

Veale and Penfrat both said there’s no way to properly assess Apple’s proposed solution because the company has not made it public. Other experts, such as Bostoen, questioned why Apple needs as long as 18 months to implement it, given the interoperability requirements were predictable and should have been addressed in parallel with the development of Siri AI.

Ultimately, Apple is playing a big game of chicken with Europe. The EU is a huge market, and Apple has every incentive to find a way to bring Siri AI there eventually, particularly as it becomes a larger part of the iPhone experience. Apple managed to put USB-C chargers in its products when Europe forced the issue. Will Europe force the AI issue with Apple now, or will Brussels be the one to blink first?

Update, June 9th: Added comments from Greg Joswiak made during a briefing after publication.

Anthropic releases its first Mythos-class model Claude Fable

2026-06-15T15:11:41-04:00

Anthropic just announced Claude Fable 5, a new AI model it said is the most powerful model it has ever made widely available.

According to the company, Fable 5 “shows exceptional performance in software engineering, knowledge work, and vision,” with its lead over other models growing as tasks become longer and more complex.

Fable 5 marks the first broad release from Anthropic’s Mythos class of AI models, after the company said the family was so capable at cybersecurity tasks that it was too dangerous to release publicly. Anthropic said the release was “made possible by new safeguards that block responses in specific high-risk areas,” with the system falling back to Claude Opus 4.8 — a model it praised for “honesty” when it launched last month.

Anthropic singled out cybersecurity and biology as two domains where the safeguards may block responses, both areas widely considered sensitive topics for advanced AI systems. The company said that in testing, 95 percent of Fable sessions ran entirely on Fable responses, without falling back to Opus 4.8.

The company is also releasing Claude Mythos 5, but provided few details on what that means. In a blog, Anthropic said Mythos 5 is the same underlying model as Fable 5, “but with the safeguards lifted in some areas.” For now, access appears limited to the steadily expanding group of organizations granted access to Claude Mythos Preview through Anthropic’s — not entirely watertight — private Project Glasswing initiative. Those users will be able to upgrade to Mythos 5, Anthropic said, adding that it plans to “expand access over time through a more systematic trusted-access program.”

Anthropic did not respond on the record to The Verge’s request for comment explaining how either model relates to Claude Mythos Preview or why the models are numbered “5” when there do not appear to be any previously released Mythos or Fable models.

Pricing for both models is significantly higher than its former flagship model — double rates for Claude Opus 4.8, though it’s half what users pay for Mythos Preview — at $10 per million input tokens and $50 per million output tokens, Anthropic said.

Uber tells London to get ready for robotaxis

2026-06-08T09:52:05-04:00

Uber is getting ready to put robotaxis on London’s streets, opening an interest list for riders who want to be among the first to hail one of Wayve’s autonomous vehicles when the service goes live later this year. The rollout would be a milestone in one of Uber’s biggest markets and an early test of whether there’s appetite for driverless ridehailing beyond the US and China, where robotaxis are already carrying passengers.

The company is asking Londoners to show their interest in being among the first public passengers in its cobranded Uber x Wayve driverless cars. In the Uber app settings, customers can sign up by selecting “join interest list” in the “autonomous vehicles” section of “ride preferences.” Uber says joining the list will “increase their chances of being matched with a Wayve autonomous vehicle at launch” and keep them updated on the service launch.

Neither Uber nor Wayve, a British startup based in London, would give an exact launch date, though both companies said the service will go live “in the coming months.” Customers matched with a Wayve vehicle will be notified in the Uber app and given the option to switch to a nonautonomous vehicle ride. Uber says riders requesting UberX, Uber Electric, or Uber Comfort will pay the same rate, with “no additional cost” for taking the autonomous vehicle.

Uber and Wayve are positioning the launch as a phased rollout rather than a citywide robotaxi service launch, with negotiations on scope and scale still ongoing with local authorities. Both declined to say which parts of London the vehicles would cover or how large the fleet would be, though Wayve’s Victor Charoonsophonsak told The Verge it would start with a mid-to-high single-digit number of cars.

The first rides will also not be fully driverless. Local regulations currently require the vehicles to have a safety driver behind the wheel, ready to take over if needed. Uber and Wayve would not say when those drivers would be removed.

Even with those limits, Uber’s interest list adds momentum to efforts to bring robotaxis to London’s roads. The UK currently doesn’t have any fully driverless vehicles on public roads, though several companies are testing them. The government has said fully driverless ridehail pilots can begin from spring 2026, though more full rollouts won’t come until late 2027, when the Automated Vehicles Act of 2024 fully takes effect.

Uber and Wayve are not alone in targeting London. Uber has also partnered with Chinese giant Baidu, while Alphabet-owned Waymo has also said it plans to launch a service in the city.

AI ‘content creators’ are getting harder to spot

2026-06-04T14:31:15-04:00

Aitana Lopez, AI avatar by creative agency The Clueless. | Image: The Clueless

This is The Stepback, a weekly newsletter breaking down one essential story from the tech world. For more on AI confusion, follow Robert Hart. The Stepback arrives in our subscribers’ inboxes at 8AM ET. Opt in for The Stepback here.

How it started

At first, AI influencers were relatively easy to identify — and to ignore. Aside from the occasional bursts of hype, they didn’t seem to change much about the way social media worked. The earliest virtual influencers — Lil Miquela with her blunt fringe and freckles, Imma with her bubblegum pink bob, and Shudu Gram with her flawless complexion — were obviously digital productions. Collaborations were announced with fanfare. Posts required studios, money, coordination, and a lot of polish.

Over time, I’ve noticed that the fake people on my timeline have started looking more and more like everyone else on it. Characters like Emily Pellegrini and Aitana Lopez moved a bit closer to reality — or at least to the reality of that well-traveled, well-off friend from college you didn’t keep in touch with, forever posting from nice restaurants and beautiful places, or from Coachella and Wimbledon. Not exactly relatable, but, then again, most professional influencers aren’t either.

Even then, many of these accounts aren’t standard ones by any means. Lopez is the product of a Spanish creative agency called The Clueless, which manages a stable of AI influencers. Pellegrini’s creator, who goes by the pseudonym Professor EP, told me he used to manage OnlyFans creators. Now he sells courses teaching people how to make AI influencers of their own.

Which is exactly what people are starting to do. A lot of people.

How it’s going

The novelty has worn off. Early AI influencers stood out because there were so few of them. Now they are part of a much larger mess of AI-generated content inundating social media: low-quality drivel lazily copied from chatbots, slop images and videos, and that catchy Lord of the Rings disco song that took over my TikTok for a month.

The fake people are now everywhere. They’re upselling drop-ship junk, scamming men out of money with fake photos, pushing disinformation and racist talking points, and catering to an increasingly weird, often sexual niche. Of course, there are a lot of thirst traps. There’s also a lot of mundane content, with avatars simply copying whatever’s popular among human creators, often just putting their fake faces on it.

That makes the scale of AI content creator influence hard to gauge. Platforms do not publish figures on how many of their users are fake people, and most AI avatars don’t become popular or influential enough to justify the kind of media attention the earlier wave received. Databases like Virtual Humans track hundreds of popular avatars, but those are only the accounts strange, weird, or big enough to get noticed. Below them is an ocean of accounts flying totally under the radar.

Part of the reason these accounts are able to avoid detection is that the technology used to make them has improved massively. A still image of a fake person can now be good enough to pass as genuine at a glance, especially in a feed filled with real influencers making generous use of staging, filters, and editing effects. Video and audio are quickly catching up, giving virtual people voices and movements that could fool undiscerning scrollers. The tools are no longer niche or prohibitively expensive, either. Mainstream products from companies like Google and OpenAI sit alongside specialized services from firms like Higgsfield, HeyGen, and ElevenLabs. With a little effort, almost anyone can make an AI influencer — or stable of them — without needing a studio, specialized equipment, or (much) money.

All this leaves social media platforms with a problem they do not seem especially interested in solving head-on. After several years of grappling with AI-generated images, videos, and audio, most major platforms now have some kind of policy covering synthetic media. But beyond requiring labels for AI-generated content, such rules often amount to little more than shoehorning the material into existing categories covering things like scams, spam, impersonation, and graphic material. AI people, especially those designed to behave like real people, don’t fit neatly into any of these buckets. They are not necessarily running a scam, posting graphic content, or impersonating someone — who would they even impersonate? And if they disclose that their posts are AI-generated, it’s not obvious what rules they’d be breaking.

For now, platforms seem content to live in ambiguity, neither fully welcoming nor shunning AI creators. They have cultivated a contradictory position, promoting AI as a creative tool while also trying to stop a tidal wave of slop from overwhelming their services. YouTube, TikTok, Instagram, and other platforms have developed rules for labeling synthetic media, particularly the realistic kind, while also promoting their own suites of AI tools, including some that can clone or simulate users. But those rules tend to focus on individual posts rather than the accounts and personas behind them, leaving AI influencers in a gray area.

In that uncertainty, the AI influencer ecosystem is thriving. Some market research firms estimate the virtual influencer market could be worth more than $60 billion by 2030, up from around $12 billion this year. Cultural clout is growing too. There are AI influencer awards, beauty pageants, dedicated talent agencies representing synthetic creators, and a booming market of synthetic creators selling courses and tools promising to help people make and run fake creators of their own, often with the promise of faceless passive income. Some of it has the faintly pyramidal smell of an online gold rush, a few visible success stories and an awful lot of people selling shovels.

What happens next

My guess is that a reckoning is on the way. AI slop is already irritating, and there’s only so much of it a platform can carry until it is rendered practically unusable, especially given their persistent refusal to let users filter AI slop. Fake people pretending to be real are an even more intimate version of the same problem. But beyond labels and enforcement of existing rules, platforms mostly seem content to see what happens. To platforms, engagement is still engagement, whether it comes from a fake creator or a real one. So long as synthetic creators keep posting and don’t stray outside of existing rules, there seems to be little incentive to crack down.

There’s also a question of how sustainable the whole idea of having AI avatars running around online is. If so many are built just to make money from human users, what happens when the pool of human users dries up? There’s only so many people who will be willing to buy courses and tools to build influencers of their own, for example. That’s presuming social media can survive the influx of AI influencers. By definition, it requires some critical mass of humanity to keep things social. If left unchecked, networks will collapse under the weight of these fake people, as human users are inevitably driven away.

That could change if public anger keeps building. Backlash over deepfakes, impersonation, and synthetic spam is already forcing lawmakers and regulators to pay closer attention, particularly after incidents involving nonconsensual sexual deepfakes generated with tools like Grok. Europe’s AI Act could be a driver, at least as its transparency obligations for AI-generated content come into force. The regulations will require deployers of generative AI systems to clearly disclose AI-generated or manipulated content, which could pressure companies to step up flagging AI content or face potentially hefty fines. But even then, the focus is still largely on content, not whether the account posting it represents an actual person.

As with so much on social media, the burden falls back on users. Many platforms have effectively delegated the task of moderating AI content to users, relying on them to spot and report suspicious profiles. But self-moderation is a poor and unsustainable answer to something designed to evade notice. There is already a growing appetite for AI-free spaces. If platforms refuse to draw boundaries between real and unreal themselves, I expect users will draw them instead.

By the way

A lot of the more high-profile AI influencers I’ve encountered recently have had an overtly political bent, which I feel could hasten the regulatory reckoning. Danny Bones, a fake white nationalist rapper funded by a far-right political party in the UK, is perhaps the best example of this I’ve seen so far.
Like human influencers, many AI avatars are built around specific identities and communities, such as race, disability, politics, and nationality, like MAGA fantasy girl Jessica Foster, who leans heavily into sexualized Army aesthetics and Trumpism. Not all avatars align with their creators: Black AI model Shudu Gram, for example, was made by a white man. Emily Pellegrini is also the product of a man, Professor EP, who told me the character is built using content he licensed from an anonymous OnlyFans creator.

Read this

The headline of Jess Weatherbed’s recent story for The Verge says it all: “Let us filter AI slop, you cowards.”
The Verge recently reported that grifters are using AI avatars of fake Black people to hawk mass-produced products via drop shipping at inflated prices on social media.
Wired reported on the booming “AI Pimping” industry, where human creators are having their content stolen and monetized by AI avatars without their permission.
Charlie Warzel’s podcast examined the incentives behind the proliferation of AI influencers and the exhaustion many feel when it comes to caring whether what we consume is real or not anymore.